Portfolio Data Science Innovator

hace 6 días


Madrid, Madrid, España Ontologize, Inc. A tiempo completo

**About the Role

We are seeking a skilled data scientist to join our Actuarial Portfolio Management, Credit and Surety team. As a key member of this team, you will contribute to the analysis of the credit and surety portfolio from both risk and profitability perspectives. You will work with internal and external data, applying advanced statistical models and machine learning techniques to optimize underwriting efficiency and drive business outcomes.

**Key Responsibilities:

  • Contribute to steering and monitoring the portfolio in line with strategic objectives
  • Support activities related to the elaboration and implementation of the strategy for Actuarial Portfolio Management Credit & Surety
  • Collaborate with cross-functional teams to develop innovative solutions that support data transformation, risk management, and underwriting efficiency

**About the Team

Our team is dedicated to providing top-notch support to our clients and driving business success through data-driven insights. We value collaboration, innovation, and continuous learning, and we are committed to creating an inclusive and diverse work environment.

**About You

To succeed in this role, you should have strong analytical and problem-solving skills, as well as excellent communication and interpersonal skills. You should be able to handle multiple priorities and meet deadlines, and you should have experience working with large datasets and developing NLP solutions.

**Requirements:

  • 6+ years of hands-on experience with PySpark and Python, particularly in building and optimizing large-scale data transformation pipelines
  • 3+ years of SQL experience, comfortable writing and optimizing complex queries
  • Solid experience developing NLP solutions, with exposure to GenAI and unsupervised learning methodologies
  • Extensive experience in data visualization and developing interactive dashboards for business stakeholders
  • Good understanding of statistical models and core statistical methods
  • Solid academic education (university degree or higher), ideally in financial economics, statistics, econometrics, financial engineering, or actuarial sciences
  • Advanced English communication skills, both written and verbal


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